Diagnostics Platform for Mitochondrial Dysfunctions/Diseases

Abstract

The present invention concerns machine learning based methods and systems for diagnosing and treating genetic diseases characterized by mitochondrial dysfunctions. A library of reference learning models is developed based on in vitro reference samples obtained from cell-cultures exposed to specific mitochondrial inhibitors. Each model is able to predict a specific labeled mitochondrial dysfunction induced in the cell-culture by the inhibitor / stressor. The reference models are then applied to target samples drawn in vivo from target subjects who are known to have specific genetic mitochondrial diseases. A mapping is developed between mitochondrial dysfunctions predicted in the subjects and their known mitochondrial diseases. This mapping and the reference models are then applied to a clinical sample of an undiagnosed patient in whom a diagnosis of a mitochondrial dysfunction and an associated mitochondrial disease is made. If there is a known rescuer for the mitochondrial dysfunction, it may be recommended in a personalized, targeted therapy.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]The present application is related to U.S. patent application Ser. No. 15 / 785,415 filed on Oct. 16, 2017 under the title “Redox-related context adjustments to a bioprocess monitored by learning systems and methods based on redox indicators”, which is a continuation-in-part of U.S. patent application Ser. No. 15 / 675,364 filed on Aug. 11, 2017 under the title “Distributed systems and methods for learning about a bioprocess from redox indicators and local conditions”.[0002]The present application is also related to U.S. Provisional Patent Application 62 / 544,749 filed on Aug. 11, 2017 under the title “Monitoring and control of electron balance in bioreactor systems” and U.S. Provisional Patent Application 62 / 621,394 filed on Jan. 24, 2018 under the title “Improved diagnostic systems and methods for poorly characterized syndromes and biological entities based on bioprocess learning models”.[0003]All the above numbered applications are incorpor...

AI Technical Summary

Benefits of technology

The present invention is a diagnostic platform that can diagnose and prescribe therapeutic strategies for genetic diseases caused by mitochondrial dysfunctions. The platform uses a learning phase to develop reference bioprocess models by exposing reference biological entities to mitochondrial inhibitors or stresses and analyzing their biomarker measurements. These models are then used to predict mitochondrial dysfunctions in target samples obtained from patients with genetic mitochondrial diseases. The platform can also suggest potential diagnoses based on the mapping of mitochondrial dysfunctions to genetic data or patterns expressed by patients. The technical effects of the invention include improved diagnosis and treatment of mitochondrial diseases and the development of a novel diagnostic platform that can predict and prescribe therapeutic strategies for these diseases.

Problems solved by technology

The bioprocesses that these biological entities undergo are extremely varied and highly complex.

Reconstruction from the genome information of the overall cell proteins and structure is not sufficient to tell us what regulatory processes are active at shorter time scales, e.g., in the physical chemistry layer.

They can cause debilitating physical, developmental, and cognitive disabilities.

They are progressive and there is no cure.

Symptoms include poor growth, loss of muscle coordination, muscle weakness, pain and seizures.

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